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Local Use-Dependent Sleep in Wakefulness Links Performance Errors to Learning

机译:清醒时本地使用相关的睡眠将性能错误与学习联系起来

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摘要

Sleep and wakefulness are no longer to be considered as discrete states. During wakefulness brain regions can enter a sleep-like state (off-periods) in response to a prolonged period of activity (local use-dependent sleep). Similarly, during nonREM sleep the slow-wave activity, the hallmark of sleep plasticity, increases locally in brain regions previously involved in a learning task. Recent studies have demonstrated that behavioral performance may be impaired by off-periods in wake in task-related regions. However, the relation between off-periods in wake, related performance errors and learning is still untested in humans. Here, by employing high density electroencephalographic (hd-EEG) recordings, we investigated local use-dependent sleep in wake, asking participants to repeat continuously two intensive spatial navigation tasks. Critically, one task relied on previous map learning (Wayfinding) while the other did not (Control). Behaviorally awake participants, who were not sleep deprived, showed progressive increments of delta activity only during the learning-based spatial navigation task. As shown by source localization, delta activity was mainly localized in the left parietal and bilateral frontal cortices, all regions known to be engaged in spatial navigation tasks. Moreover, during the Wayfinding task, these increments of delta power were specifically associated with errors, whose probability of occurrence was significantly higher compared to the Control task. Unlike the Wayfinding task, during the Control task neither delta activity nor the number of errors increased progressively. Furthermore, during the Wayfinding task, both the number and the amplitude of individual delta waves, as indexes of neuronal silence in wake (off-periods), were significantly higher during errors than hits. Finally, a path analysis linked the use of the spatial navigation circuits undergone to learning plasticity to off periods in wake. In conclusion, local sleep regulation in wakefulness, associated with performance failures, could be functionally linked to learning-related cortical plasticity.
机译:睡眠和清醒不再被视为离散状态。在清醒期间,大脑区域可能会因长时间的活动(依赖于局部使用的睡眠)而进入类似睡眠的状态(休息时间)。类似地,在非快速眼动睡眠期间,慢波活动(睡眠可塑性的标志)在先前参与学习任务的大脑区域中局部增加。最近的研究表明,在任务相关区域的休假期间,行为表现可能会受到影响。但是,人类尚未测试唤醒后休假期,相关的性能错误和学习之间的关系。在这里,通过采用高密度脑电图(hd-EEG)记录,我们研究了唤醒后局部使用相关的睡眠,要求参与者连续重复两次密集的空间导航任务。至关重要的是,一项任务依赖于以前的地图学习(寻路),而另一项任务则没有(控制)。行为清醒的参与者(没有被剥夺睡眠)仅在基于学习的空间导航任务期间显示增量活动的逐渐增加。如源定位所示,三角洲活动主要定位在左顶叶和双侧额叶皮层,所有区域都从事空间导航任务。此外,在寻路任务期间,这些增量功率增量与错误特别相关,与控制任务相比,其发生概率明显更高。与“寻路”任务不同,在“控制”任务期间,增量活动和错误数量均不会逐渐增加。此外,在“寻路”任务期间,作为错误(唤醒时间)(休止期)神经元沉默的指标,单个三角洲波的数量和幅度都比击中时高得多。最后,路径分析将学习可塑性的空间导航电路的使用与唤醒后的关闭时间联系起来。总之,清醒时与性能衰竭相关的局部睡眠调节可能在功能上与学习相关的皮质可塑性有关。

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